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- Coatings | Aims Scope - MDPI
Coatings (ISSN 2079-6412) is an international, peer-reviewed and open access journal devoted to the science and engineering of coatings, thin and thick films, surfaces and interfaces
- Coatings | An Open Access Journal from MDPI
This study fabricated six types of NiCr–Cr 3 C 2 composite coatings using high-velocity oxygen fuel (HVOF) spraying and systematically evaluated their tribological behavior at 350 °C and 500 °C, along with their electrochemical corrosion performance in 3 5 wt % NaCl solution
- Coatings | Editorial Board - MDPI
Interests: coatings for cutting tools and machine elements, FEA modelling; superficial treatments; characterization of coated tool's strength, fatigue and adhesion properties
- Coatings | Special Issues - MDPI
Coatings publishes Special Issues to create collections of papers on specific topics, with the aim of building a community of authors and readers to discuss the latest research and develop new ideas and research directions
- All Sections | Coatings | MDPI
The section “Liquid–Fluid Coatings, Surfaces and Interfaces” is a platform devoted to the science and engineering of complex fluids confined in the vicinity of interfaces or surfaces
- Coatings | Instructions for Authors - MDPI
Manuscripts for Coatings should be submitted online at susy mdpi com The submitting author, who is generally the corresponding author, is responsible for the manuscript during the submission and peer review process
- Coatings | Article Processing Charges - MDPI
All articles published in Coatings (ISSN 2079-6412) are published in full open access An article processing charge (APC) of CHF 2600 (Swiss francs) applies to papers accepted after peer review
- Machine Learning-Driven Advancements in Coatings - MDPI
The integration of machine learning (ML) into the field of coatings presents unprecedented opportunities for innovation and advancement, driving a significant shift in how we approach the design, development, and application of these materials
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